code: def test_load_to_cuda(options):
      reader = MockDatasetReader()
      loader = MultiProcessDataLoader(
          reader=reader,
          data_path="this doens't matter",
          cuda_device=0,
          **options,
      )
      vocab = Vocabulary.from_instances(loader.iter_instances())
      loader.index_with(vocab)
      for batch in loader:
          assert batch["tensor"].device == torch.device("cuda:0")
  
imports: from typing import List, Iterable, Dict
  import torch
  import pytest
  from allennlp.common.testing import requires_gpu
  from allennlp.data.instance import Instance
  from allennlp.data.dataset_readers import DatasetReader
  from allennlp.data.data_loaders import MultiProcessDataLoader, WorkerError
  from allennlp.data.fields import Field, TextField, MetadataField, TensorField
  from allennlp.data.tokenizers import PretrainedTransformerTokenizer
  from allennlp.data.token_indexers import PretrainedTransformerIndexer
  from allennlp.data.vocabulary import Vocabulary
  from allennlp.data.data_loaders.data_collator import LanguageModelingDataCollator
label_desc: Use image node_id 6 for calling a global function with example usage: test_load_to_cuda(options) without return types